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217 lines
9.2 KiB
Python
217 lines
9.2 KiB
Python
from PIL import Image, ImageEnhance, ImageOps
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import numpy as np
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import random
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# Non-random random
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random.seed(0)
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class BasicPolicy(object):
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def __init__(self, mirror_ratio = 0, flip_ratio = 0, color_change_ratio = 0, is_full_set_colors = False, add_noise_peak = 0.0, erase_ratio = -1.0):
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# Random color channel order
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from itertools import product, permutations
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self.indices = list(product([0,1,2], repeat = 3)) if is_full_set_colors else list(permutations(range(3), 3))
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self.indices.insert(0, [0,1,2]) # R,G,B
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self.add_noise_peak = add_noise_peak
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# Mirror and flip
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self.color_change_ratio = color_change_ratio
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self.mirror_ratio = mirror_ratio
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self.flip_ratio = flip_ratio
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# Erase
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self.erase_ratio = erase_ratio
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def __call__(self, img, depth):
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# 0) Add poisson noise (e.g. choose peak value 20)
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# https://stackoverflow.com/questions/19289470/adding-poisson-noise-to-an-image
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if self.add_noise_peak > 0:
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PEAK = self.add_noise_peak
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img = np.random.poisson(np.clip(img, 0, 1) * PEAK) / PEAK
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# 1) Color change
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policy_idx = random.randint(0, len(self.indices) - 1)
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if random.uniform(0, 1) >= self.color_change_ratio:
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policy_idx = 0
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img = img[...,list(self.indices[policy_idx])]
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# 2) Mirror image
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if random.uniform(0, 1) <= self.mirror_ratio:
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img = img[...,::-1,:]
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depth = depth[...,::-1,:]
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# 3) Flip image vertically
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if random.uniform(0, 1) < self.flip_ratio:
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img = img[...,::-1,:,:]
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depth = depth[...,::-1,:,:]
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# 4) Erase random box
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if random.uniform(0, 1) < self.erase_ratio:
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img = self.eraser(img)
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return img, depth
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def __repr__(self):
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return "Basic Policy"
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def eraser(self, input_img, p=0.5, s_l=0.02, s_h=0.4, r_1=0.3, r_2=1/0.3, v_l=0, v_h=255, pixel_level=True):
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img_h, img_w, img_c = input_img.shape
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p_1 = np.random.rand()
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if p_1 > p:
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return input_img
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while True:
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s = np.random.uniform(s_l, s_h) * img_h * img_w
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r = np.random.uniform(r_1, r_2)
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w = int(np.sqrt(s / r))
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h = int(np.sqrt(s * r))
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left = np.random.randint(0, img_w)
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top = np.random.randint(0, img_h)
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if left + w <= img_w and top + h <= img_h:
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break
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if pixel_level:
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c = np.random.uniform(v_l, v_h, (h, w, img_c))
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else:
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c = np.random.uniform(v_l, v_h)
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input_img[top:top + h, left:left + w, :] = c
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return input_img
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def debug_img(self, img, depth, idx, i, prefix=''):
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from PIL import Image
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aug_img = Image.fromarray(np.clip(np.uint8(img*255), 0, 255))
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aug_img.save(prefix+str(idx)+"_"+str(i)+'.jpg',quality=99)
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aug_img = Image.fromarray(np.clip(np.uint8(np.tile(depth*255,3)), 0, 255))
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aug_img.save(prefix+str(idx)+"_"+str(i)+'.depth.jpg',quality=99)
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#
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# Original code at https://github.com/DeepVoltaire/AutoAugment
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#
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class ImageNetPolicy(object):
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""" Randomly choose one of the best 24 Sub-policies on ImageNet.
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Example:
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>>> policy = ImageNetPolicy()
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>>> transformed = policy(image)
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Example as a PyTorch Transform:
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>>> transform=transforms.Compose([
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>>> transforms.Resize(256),
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>>> ImageNetPolicy(),
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>>> transforms.ToTensor()])
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"""
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def __init__(self, fillcolor=(128, 128, 128)):
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self.policies = [
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SubPolicy(0.4, "posterize", 8, 0.6, "rotate", 9, fillcolor),
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SubPolicy(0.6, "solarize", 5, 0.6, "autocontrast", 5, fillcolor),
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SubPolicy(0.8, "equalize", 8, 0.6, "equalize", 3, fillcolor),
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SubPolicy(0.6, "posterize", 7, 0.6, "posterize", 6, fillcolor),
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SubPolicy(0.4, "equalize", 7, 0.2, "solarize", 4, fillcolor),
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SubPolicy(0.4, "equalize", 4, 0.8, "rotate", 8, fillcolor),
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SubPolicy(0.6, "solarize", 3, 0.6, "equalize", 7, fillcolor),
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SubPolicy(0.8, "posterize", 5, 1.0, "equalize", 2, fillcolor),
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SubPolicy(0.2, "rotate", 3, 0.6, "solarize", 8, fillcolor),
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SubPolicy(0.6, "equalize", 8, 0.4, "posterize", 6, fillcolor),
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SubPolicy(0.8, "rotate", 8, 0.4, "color", 0, fillcolor),
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SubPolicy(0.4, "rotate", 9, 0.6, "equalize", 2, fillcolor),
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SubPolicy(0.0, "equalize", 7, 0.8, "equalize", 8, fillcolor),
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SubPolicy(0.6, "invert", 4, 1.0, "equalize", 8, fillcolor),
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SubPolicy(0.6, "color", 4, 1.0, "contrast", 8, fillcolor),
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SubPolicy(0.8, "rotate", 8, 1.0, "color", 2, fillcolor),
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SubPolicy(0.8, "color", 8, 0.8, "solarize", 7, fillcolor),
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SubPolicy(0.4, "sharpness", 7, 0.6, "invert", 8, fillcolor),
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SubPolicy(0.6, "shearX", 5, 1.0, "equalize", 9, fillcolor),
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SubPolicy(0.4, "color", 0, 0.6, "equalize", 3, fillcolor),
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SubPolicy(0.4, "equalize", 7, 0.2, "solarize", 4, fillcolor),
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SubPolicy(0.6, "solarize", 5, 0.6, "autocontrast", 5, fillcolor),
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SubPolicy(0.6, "invert", 4, 1.0, "equalize", 8, fillcolor),
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SubPolicy(0.6, "color", 4, 1.0, "contrast", 8, fillcolor)
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]
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def __call__(self, img):
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policy_idx = random.randint(0, len(self.policies) - 1)
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return self.policies[policy_idx](img)
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def __repr__(self):
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return "AutoAugment ImageNet Policy"
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class SubPolicy(object):
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def __init__(self, p1, operation1, magnitude_idx1, p2, operation2, magnitude_idx2, fillcolor=(128, 128, 128)):
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ranges = {
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"shearX": np.linspace(0, 0.3, 10),
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"shearY": np.linspace(0, 0.3, 10),
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"translateX": np.linspace(0, 150 / 331, 10),
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"translateY": np.linspace(0, 150 / 331, 10),
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"rotate": np.linspace(0, 30, 10),
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"color": np.linspace(0.0, 0.9, 10),
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"posterize": np.round(np.linspace(8, 4, 10), 0).astype(np.int),
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"solarize": np.linspace(256, 0, 10),
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"contrast": np.linspace(0.0, 0.9, 10),
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"sharpness": np.linspace(0.0, 0.9, 10),
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"brightness": np.linspace(0.0, 0.9, 10),
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"autocontrast": [0] * 10,
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"equalize": [0] * 10,
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"invert": [0] * 10
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}
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# from https://stackoverflow.com/questions/5252170/specify-image-filling-color-when-rotating-in-python-with-pil-and-setting-expand
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def rotate_with_fill(img, magnitude):
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rot = img.convert("RGBA").rotate(magnitude)
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return Image.composite(rot, Image.new("RGBA", rot.size, (128,) * 4), rot).convert(img.mode)
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func = {
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"shearX": lambda img, magnitude: img.transform(
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img.size, Image.AFFINE, (1, magnitude * random.choice([-1, 1]), 0, 0, 1, 0),
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Image.BICUBIC, fillcolor=fillcolor),
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"shearY": lambda img, magnitude: img.transform(
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img.size, Image.AFFINE, (1, 0, 0, magnitude * random.choice([-1, 1]), 1, 0),
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Image.BICUBIC, fillcolor=fillcolor),
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"translateX": lambda img, magnitude: img.transform(
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img.size, Image.AFFINE, (1, 0, magnitude * img.size[0] * random.choice([-1, 1]), 0, 1, 0),
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fillcolor=fillcolor),
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"translateY": lambda img, magnitude: img.transform(
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img.size, Image.AFFINE, (1, 0, 0, 0, 1, magnitude * img.size[1] * random.choice([-1, 1])),
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fillcolor=fillcolor),
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#"rotate": lambda img, magnitude: rotate_with_fill(img, magnitude),
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# "rotate": lambda img, magnitude: img.rotate(magnitude * random.choice([-1, 1])),
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"rotate": lambda img, magnitude: img,
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"color": lambda img, magnitude: ImageEnhance.Color(img).enhance(1 + magnitude * random.choice([-1, 1])),
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"posterize": lambda img, magnitude: ImageOps.posterize(img, magnitude),
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"solarize": lambda img, magnitude: ImageOps.solarize(img, magnitude),
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"contrast": lambda img, magnitude: ImageEnhance.Contrast(img).enhance(
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1 + magnitude * random.choice([-1, 1])),
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"sharpness": lambda img, magnitude: ImageEnhance.Sharpness(img).enhance(
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1 + magnitude * random.choice([-1, 1])),
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"brightness": lambda img, magnitude: ImageEnhance.Brightness(img).enhance(
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1 + magnitude * random.choice([-1, 1])),
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"autocontrast": lambda img, magnitude: ImageOps.autocontrast(img),
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"equalize": lambda img, magnitude: ImageOps.equalize(img),
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"invert": lambda img, magnitude: ImageOps.invert(img)
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}
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# self.name = "{}_{:.2f}_and_{}_{:.2f}".format(
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# operation1, ranges[operation1][magnitude_idx1],
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# operation2, ranges[operation2][magnitude_idx2])
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self.p1 = p1
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self.operation1 = func[operation1]
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self.magnitude1 = ranges[operation1][magnitude_idx1]
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self.p2 = p2
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self.operation2 = func[operation2]
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self.magnitude2 = ranges[operation2][magnitude_idx2]
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def __call__(self, img):
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if random.random() < self.p1: img = self.operation1(img, self.magnitude1)
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if random.random() < self.p2: img = self.operation2(img, self.magnitude2)
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return img |